(A) study on the implementation of the automatic white blood cell differential counting system

Abstract

An automatic white blood cell differential counting system, to be called EBIS 81 (Electronic System Lab``s Binary Image Processing System), was developed, which consists of Z-2 system, GLOPR part, and Auto searching and focusing part. This paper is divided into two part. First, a general description of classification is given to system which classifies the white blood cells into 6 types. Second, some classification methods with the simulation data quoted from the Appendix of Ref. 6 were studied. The logic classifier developed compared favorably with other conventional classifiers. Some statistical methods (e.g. Bayes classifier, Minimum distance classifier, Nearest neighbor decision, K-Nearest neighbor decision) and logic based classifier method were examined. Among others, the logic classifier based on the VVL concept has the advantage of easy hardware realization and fast decision time. At present, the classification accuracy achieved is only 80.95\% with the K-nearest neighbor decision (K=3) and 86.49\% with the Bayes, Minimum distance classifier. To get higher classification accuracy, cooperation from some clinical center is needed.